Team:ETH Zurich/ApproachA

Tethering bacteria to a glass surface
This experiment is both simple to set up and analyze. The cells were grown, as before, in M9 medium at 30°C, which yields an average of 1.5 flagella per cell[5]. This is crucial to tether most of the bacteria at only one flagellum. For highest motility, cells were harvested during the mid to late exponential growth phase and resuspended in a specific tethering medium. To truncate the flagella, the bacteria were pushed through a very thin needle. This is a necessary step so the bacteria bind to the antibody close to the membrane, which guarantees nice circular rotations. The microfluidic chip was prepared by incubating it with the antibody specific for the flagellar protein FliC. The antibody attaches to the glass surface, due to intermolecular forces with the glass’ silica surface. The bacteria with the sheared off flagella were then also incubated inside the channels overnight at 4°C to prevent cell division (see Microfluidic Chip).
Imaging the apartate response
The procedure described in this section was the proof-of-concept experiment for the viability of “Approach A: Chemotaxis” as a biosensor. It showed the bacteria reacting to step changes in concentration of the natural Tar ligand aspartate. The readout was acquired by imaging many bacteria with a 20x magnification phase contrast microscope. The low magnification allowed us to have enough resolution to resolve single spinning bacteria, while guaranteeing a high enough frame rate (25 frames per seconds) to also resolve the bacteria’s natural rotational frequency (2-9 Hz). As seen in (video of spinning bacteria) only about 5-10% were spinning, a value which agrees with literature [citation needed]. Several dilutions of aspartate ranging from 0.1 μM to 1 mM were prepared. These concentrations correspond to the natural sensing range of the Tar receptor.[citation needed] To expose the tethered cells to the different concentrations, the medium in the reservoir of the microfluidic chip was exchanged manually with a pipette. With the optimal flow rate of 10 μL/min (see Microfluidic Chip) the cells were induced resulting in the described change in rotational bias. We measured many different concentration changes; we increased from zero to low and high concentration and we made multiple stepwise increases or decreases.
The video shows an overview of multiple bacteria spinning inside the microfluidic chip.
Originally this experiment was conducted by analyzing individual cells by eye.[3] We developed an image analysis algorithm (with the help of Corey Dominick from the University of Pittsburgh Link to attributions/integrated HP) to read out the rotation of the bacteria. This is achieved by determining the position of the individual bacteria in each frame of the video, which yields the rotational angle for subsequent frames (more details Link Software/Motility analysis). From this data the adaptation times for different changes can be read out directly. This data is important for tuning our model to our data (see Model). To yield the data in a form, which can be used to control the robot, the tumbling frequency is read out before and after induction. To this end, we created an algorithm, which reads out the number of tumbles over a certain amount of time using a “sliding window” over the raw data.
Particle Standard Curve Log Scale
This figure shows the response of one bacterium to a concentration change from 0 to 100 μM. Top: This graph depicts the step increase of the aspartate concentration, which happens at 90 s after measurement start. After the medium exchange the concentration stays at this level. Middle: The graph shows the data acquired from the analysis of the bacterial rotation. The bacteria, which have been tethered to the glass surface spin either in CCW or CW direction. At the beginning of the time series the Tar receptor is fully adapted to the environmental concentration (which is 0 in this case), so it spins with its natural tumbling frequency (tumble = CW rotation). After 70 seconds the flow starts to increase for the medium exchange resulting in a forced stop in rotation. The medium containing the 100 μM aspartate reaches the bacteria at 100 s (marked with the red arrow), after which the flow rate decreases over the next 10 seconds. This results in the start of the expected rotational behavior at 110 s. Towards the end of the graph the bacteria have adapted to the new concentration. Bottom: This graph is generated from the one in the middle by calculating the CW rate using a “moving window”. This data is used as the output of the biosensor.
Particle Standard Curve Log Scale
This figure shows the chemotactic response of the tethered bacteria to a aspartate concentration change of 0 - 10 μM. The information on how to read the graphs is described in figure 4. From the bottom graph it becomes clear that the adaptation time is a lot shorter for 10 μM than for 100 μM (compare figure 4).
Follow-up experiment with 𝝰-methyl-aspartate
Considering that aspartate is a natural nutrient for E. coli, we continued the response experiment with the related compound 𝝰-methyl-aspartate. This molecule has structural similarity to aspartate and is therefore also sensed by the Tar receptor. However, it is not degraded by the bacteria. Although no response was observed for very low concentrations of 𝝰-methyl-aspartate (around 1 μM), we were still able to detect a rotational bias similar to aspartate. This proves the hypothesis that other non-nutrient molecules can be sensed by the Tar receptor.
Sticky Flagella
After promising result, we expanded on the idea of tethering bacteria to a glass surface by creating a flagellum, which sticks to objects, without an antibody as an intermediate molecule. This would make the setup even easier and cheaper to produce. The idea was to introduce a mutation in the flagellar gene fliC, which generates a fully functional but sticky version of the protein.[8,9,10] We generated the BioBrick “Sticky fliC” (BBa_K2845000) as a basic part as described in literature, as well as a composite part with the Sticky fliC under a constitutive promoter plus RBS (BBa_K2845001).
The readout of the chemotactic response of bacteria turns out to be a viable approach as a fast cell-based biosensor. The post-translational pathway allowed us to measure a signal seconds after induction with different aspartate concentrations. The big advantage of this approach is that it does not contain any artificial protein interactions but is purely based on the natural pathway of the Tar receptor, which has been optimized over millions of years of evolution. This promises the speed required for our biology-electronics interface.
  • [1] Silverman, Michael, and Melvin Simon. "Flagellar rotation and the mechanism of bacterial motility." Nature 249.5452 (1974): 73.
  • [2] Guha, Suvajyoti, et al. "Characterizing the adsorption of proteins on glass capillary surfaces using electrospray-differential mobility analysis." Langmuir 27.21 (2011): 13008-13014.
  • [3] Block, Steven M., Jeffrey E. Segall, and Howard C. Berg. "Impulse responses in bacterial chemotaxis." Cell 31.1 (1982): 215-226.
  • [4] Berg, Howard C., and P. M. Tedesco. "Transient response to chemotactic stimuli in Escherichia coli." Proceedings of the National Academy of Sciences 72.8 (1975): 3235-3239.
  • [5] Larsen, Steven H., et al. "Change in direction of flagellar rotation is the basis of the chemotactic response in Escherichia coli." Nature 249.5452 (1974): 74.
  • [6] Kuwajima, G. O. R. O. "Construction of a minimum-size functional flagellin of Escherichia coli." Journal of Bacteriology 170.7 (1988): 3305-3309.
  • [7] Berg, Howard C., and Linda Turner. "Torque generated by the flagellar motor of Escherichia coli." Biophysical journal 65.5 (1993): 2201-2216.
  • [8] Scharf, Birgit E., et al. "Control of direction of flagellar rotation in bacterial chemotaxis." Proceedings of the National Academy of Sciences 95.1 (1998): 201-206.
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